1. Field of the Invention
The present invention relates to the field of medical resource utilization including, but not limited to the scheduling of medical staff and medical facilities. More particularly, embodiments of the present invention collect and compile billing data from one or more medical billing systems and convert the billing data into historical demand information for a medical resource so as to generate a forecasted demand for the medical resource within a medical facility during a selected time period.
2. Description of Related Art
The scheduling of medical personnel, including clinicians, technicians, and other staff, and other medical resources, such as procedure rooms, is becoming increasingly complex as medical facilities grow larger and as multiple medical facilities and campuses become consolidated under a single administrative and/or ownership entity such as a health care corporation. However, in conventional health care administration systems, the scheduling of specific personnel and medical procedure space within a medical facility is largely determined by estimations based on maximum potential demand for a given resource during a selected time period.
For example, in an anesthesiology department having a number of available procedure rooms, a typical weekday may have a peak demand for procedure rooms and clinicians (which is often determined by a number of procedures (i.e. administrations of anesthesia) during a given two-hour span in the middle of the day. In conventional scheduling methods, scheduling administrators often schedule sufficient medical personnel (including anesthesiologists and certified nurse anesthetists, for example) and procedure rooms to accommodate the peak number of concurrent procedures for an entire shift (i.e. a 10-hour shift from 0700-1700), where the peak number of concurrent procedures may be occurring only during a 2 hour span in the middle of the day. However, conventional scheduling systems and techniques do not utilize concurrent activities information (such as information on a number of concurrent medical procedures during a given time period gleaned from billing data generated in a selected medical facility) that may inform a scheduling administrator of the time period in which peak demand for one or more medical resources is expected to be experienced.
Furthermore, conventional scheduling systems are not configured to distill concurrent activities information from billing data taken from one or more medical billing data systems, which may provide billing data that may be used (if properly manipulated and/or interpreted) to aid in the prediction of demand patterns for a medical resource within a medical facility during a selected time period. For example, medical billing systems often contain detailed information regarding the type of procedure performed and the clinicians and/or staff members required to perform a specific procedure. Billing data may also include time stamp information and/or duration information that may be indicative of the time required to perform a given procedure and/or the time spent by various clinicians and/or staff members to perform a given role in a medical procedure. Billing data tied to particular medical procedures may also provide a more realistic historical profile of demand for medical resources (such as medical personnel and/or medical facility space) than, for example, the historical usage of medical supplies and/or other inventory items. This may be especially true for medical procedures such as anesthesia administration, which may utilize relatively few inventoried medical disposables, but may require significant medical resources including, for example, facility space for patient preparation and patient recovery and clinicians to oversee patient preparation, administration of anesthesia, and patient recovery.
While billing data may provide a large amount of data that is generally indicative of demand for a given medical resource in a medical facility during a selected time period, such billing data is often non-standardized across medical facilities and/or across administrative entities. For example, some billing data may only include a time stamp and a procedure code indicative of a specific service performed in a medical procedure. For example, in the billing of a particular administration of anesthesia, the billing data may indicate the service codes including, but not limited to: patient preparation, anesthesia administration, surgery and/or medical procedure, and patient recovery. Even if these service codes are accompanied by a time stamp as part of a billing data set, the billing data set may not be immediately useful to a scheduling administrator, because such codes do not immediately indicate the types of personnel, the expected duration, and/or the type of procedure room required for each service. Thus, it may be necessary, in some cases, to interpret and/or convert billing data into alternative data types that may be predictive of the utilization of particular medical resources during a selected time period in order to aid a scheduling administrator in meeting a predicted demand during a future comparable time period.
Thus limitations in current scheduling systems and limitations inherent in billing data, that may otherwise aid scheduling administrators in generating more efficient schedules, may create a burden on scheduling administration systems as well as create inefficiencies that may exacerbate the already high costs of health care. Specifically, since conventional scheduling systems are not capable of retrieving billing information from a medical billing system and converting such billing information into usable scheduling data, such scheduling systems are incapable of ascertaining an accurate history of the actual demand for specific medical resources (such as procedure rooms and/or medical personnel) during a selected time period that may be predictive of demand for such resources in a comparable subsequent time period. In order to ensure that sufficient medical resources may be on hand in a given medical facility during a selected time period, scheduling administrators may be required to over-schedule personnel and facilities space to accommodate the busiest portions of a particular time period. For example, a scheduling administrator may be required to schedule sufficient medical personnel and facility space to accommodate 5 substantially concurrent medical procedures in a particular medical facility for an entire shift even though the actual demand for such medical resources may only exist (as indicated by billing data, for example) during a comparatively short time window during the middle of the shift. Conventional search systems lack the capability of accessing billing data for a selected time period, much less translating and/or converting such billing data into predictive forecast data that may be either presented to a user prior to the scheduling of medical resources for a subsequent comparable time period. Thus, some users (such as scheduling administrators and/or physicians) will be required to rely on gross estimates ascertained from “worst-case” maximum demand scenarios. Thus, conventional scheduling systems may over-schedule medical resources for the majority of a shift (or other time period) in order to ensure that sufficient resources are available in a medical facility during a particular time period.
Therefore, there exists a need for an improved system to solve the technical problems outlined above that are associated with conventional medical resource scheduling systems. More particularly, there exists a need for a system capable of converting medical billing data that may be retrieved from a medical billing system into a format that may be indicative of a historical demand for a medical resource in a particular medical facility during a selected time period. There also exists a need for a system capable of providing scheduling forecast information to a scheduling administrator (via a display, for example) such that the administrator may effectively use the converted billing data in order to generate a schedule of medical resources that is optimally matched to a predicted demand for medical resources during a selected time period. In addition, there exists a need for a system that may export a forecasted demand for medical resources (as a forecast schedule, for example) into a scheduling system and/or calendar such that the forecast schedule shown in the calendar is optimized for efficiency based at least partially upon the forecasted demand for medical resources (such as medical personnel and/or medical procedure rooms).